Policy disruption early warning system

ABSTRACT

The present disclosure is directed to a legal path analysis framework that can efficiently evaluate the impact of legislation on U.S. federal government agencies. This framework and its implementation as a database drive web application can enable policy analysts, research, government agencies, etc. to trace and visualize the path of changes to the United States Code (U.S.C.) and Code of Federal Regulations (C.F.R) as well as highlight federal agencies that are ultimately affected by these changes in the legal system.

FIELD OF THE DISCLOSURE

The present disclosure is directed to a legal path analysis frameworkthat can efficiently evaluate the impact of legislation on U.S. federalgovernment agencies. More specifically, the framework and itsimplementation can trace and visualize the path of changes to the UnitedStates Code (U.S.C.) and Code of Federal Regulations (C.F.R) as well ashighlight federal agencies that are ultimately affected by these changesin the legal system.

BACKGROUND

The United States (U.S.) legal system includes several major bodies oflegal texts which outline the authorities and responsibilities offederal government agencies such as the IRA, VA, DISA, Air Force, GPO,CTH, USAID, FAA, and DOD. Congress can introduce and pass various billsand resolutions which can affect the scope of these federal agencies.These enacted bills become public laws and a part of the United StatesCode (U.S.C.) is modified to incorporate these public law. These changesto the U.S.C. can create and eliminate agencies, modify their funding,and/or expand or contract their jurisdiction. One of the main roles offederal agencies is to execute and enforce the laws of the U.S.government. The federal agencies must update their rules and regulationsin the Code of Federal Regulations (C.F.R.) to abide by any changes tothe U.S.C. Besides updating the C.F.R., the federal agencies can alsomake changes to their internal policy documents.

Since 1973, there have been over 11,000 enacted public laws averagingabout 500 per year. The U.S.C. alone contains over 47,000 pages of textand over 43 million words. In addition, federal agencies and variousdepartments issue around 8,000 federal regulations each year.Accordingly, the collective legal corpora are immense, complex, andconstantly changing.

SUMMARY

Federal agencies have to implement and comply with the collective legalbodies of immense, complex, and constantly changing text. As such, theseagencies need to identify any updates to the law and implement them intotheir regulations and policies. However, forecasting the potentialimpact of newly passed legislation on the greater legal system and thegovernment agencies that the legislation regulates is difficult due tothe multiple cross-referenced layers of immense legal corpora. In fact,many agencies manually search the newly passed legislation with guidancefrom their legal department in order to determine the impact thelegislation has on the agency. In addition, searching these vast andever changing bodies of legal text is computationally inefficient.Furthermore, the interplay between the laws, regulations, and policiesand the various government agencies is hard to visualize as there is noclear diagram for showing how the laws work together.

Applicants have discovered a legal path analysis framework that canefficiently evaluate the impact of legislation on U.S. federalgovernment agencies. This framework and its implementation as a databasedriven web application can enable policy analysts, research, governmentagencies, etc. to trace and visualize the path of changes to the UnitedStates Code (U.S.C.) and Code of Federal Regulations (C.F.R) as well ashighlight federal agencies that are ultimately affected by these changesin the legal system. Applicants discovered that citations betweenclasses of legal documents can indicate procedural dependencies. Assuch, Applicants created a legal citation network from open data onlaws, regulations, and policies (LRP) to model their interdependenciesand interactions with federal agencies. Specifically, Applicants modeledthe various legal documents as nodes in a network and the citationsbetween the documents as edges in the network. Content and topics fromthe legal documents can be extracted to make them searchable. As such,Applicants' network can answer various legal queries.

By using this legal citation network, Applicants discovered a way toconstruct an early warning system for potential disruptions to agencies'existing policies and programs that can be handled by a computer moreefficiently. In addition, Applicants built interfaces to allow users tomonitor changes in LRPs and understand the impact on a given agency. Theinterface can allow users to search the legal citation network by topicand topology as well as perform case studies.

Some embodiments include a method for determining the impact of at leastone federal public law on a federal agency, the method comprising:creating a citation network comprising: creating a node for at least onefederal agency; a node for at least one title of the Code of FederalRegulations (CFR), a node for at least one title of the Code of Laws ofthe United States of America (U.S.C.), and a node for at least onefederal public law; determining titles of the CFR that are relevant tothe at least one federal agency; in response to determining titles ofthe CFR that are relevant to the at least one federal agency, creatingan edge between the corresponding determined CFR title node and thecorresponding federal agency node; determining citations to the U.S.C.in the CFR; in response to determining a citation to the U.S.C. in theCFR, creating an edge between the corresponding cited U.S.C. title nodeand the corresponding CFR title node; determining citations to federalpublic laws in the U.S.C.; and in response to determining a citation tofederal public laws, creating an edge between the corresponding citedfederal public law node and the U.S.C. title node; and determining thefederal agency associated with the at least one federal public law usingthe citation network.

In some embodiments, determining the federal agency associated with theat least one federal public law using the citation network comprisesdetermining if edges exist: between the node of the at least one federalpublic law and a node of a U.S.C. title; between the node of the U.S.C.title and a node of a C.F.R. title; and between the node of the C.F.R.title and a node of the federal agency. In some embodiments, in responseto determining that the edges exist between the node of the at least onefederal public law and the node of the U.S.C. title, between the node ofthe U.S.C. title and the node of the C.F.R. title, and between the nodeof the C.F.R. title and the node of the federal agency, displaying theedges and nodes between the at least one federal public law, the U.S.C.title, the C.F.R. title, and the federal agency. In some embodiments,determining titles of the CFR that are relevant to the at least onefederal agency comprises determining federal agencies that are named inC.F.R. titles. In some embodiments, determining titles of the CFR thatare relevant to the at least one federal agency comprises determiningcitations to C.F.R. titles in rules in the Federal Register andconnecting a federal agency to a specific C.F.R. title cited in a rulein the Federal Register issued by the federal agency. In someembodiments, the method further comprises receiving a request todetermine the impact of a first federal public law on a first federalagency. In some embodiments, in response to receiving a request todetermine the impact of the first federal public law on the firstfederal agency, displaying a legal citation network comprising: an edgebetween a node of a first U.S.C. title and a node of the first federalpublic law cited in a section of the U.S.C. under the first U.S.C.title; an edge between a node of a first C.F.R. title and the node ofthe first U.S.C. title cited in a section of the C.F.R. under the firstC.F.R. title; and an edge between a node of a first federal agency andthe node of the first C.F.R. title that is relevant to the first federalagency.

In some embodiments, creating a citation network further comprises:creating a node for a federal bill; determining citations to the U.S.C.in the federal bill; and in response to determining a citation to theU.S.C. in the federal bill, creating an edge between the correspondingcited U.S.C. title node and the federal bill node. In some embodiments,the method further comprises determining a federal agency associatedwith the federal bill using the citation network. In some embodiments,creating a citation network further comprises: creating a node for anExecutive Order; determining citations to the C.F.R. in the ExecutiveOrder; and in response to determining a citation to the C.F.R. in theExecutive Order, creating an edge between the corresponding cited C.F.R.title node and the Executive Order node. In some embodiments, the methodfurther comprises determining each federal agency associated with theExecutive Order using the citation network.

Some embodiments include a nontransitory computer readable storagemedium storing one or more programs, the one or more programs comprisinginstructions, which when executed by an electronic device, cause thedevice to perform the methods described above and herein. Someembodiments include an electronic device comprising one or moreprocessors; memory; and one or more programs, wherein the one or moreprograms are stored in the memory and are configured to be executed bythe one or more processors, the one or more programs includinginstructions for performing the methods described above and herein.

Some embodiments include an electronic device comprising one or moreprocessors; memory; and one or more programs, wherein the one or moreprograms are stored in the memory and configured to be executed by theone or more processors, the one or more programs including instructionsfor any of the methods described above. Some embodiments include anontransitory computer readable storage medium storing one or moreprograms, the one or more programs comprising instructions, which whenexecuted by an electronic device, cause the device to perform any of themethods described above.

As used herein, the singular forms “a,” “an,” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It is also to be understood that the term “and/or” as usedherein refers to and encompasses any and all possible combinations ofone or more of the associated listed items. It is further to beunderstood that the terms “includes, “including,” “comprises,” and/or“comprising,” when used herein, specify the presence of stated features,integers, steps, operations, elements, components, and/or units but donot preclude the presence or addition of one or more other features,integers, steps, operations, elements, components, units, and/or groupsthereof.

Unless specifically stated otherwise as apparent from the followingdiscussion, it is appreciated that, throughout the description,discussions utilizing terms such as “processing,” “computing,”“calculating,” “determining,” “displaying,” “obtaining,” “identifying,”or the like, refer to the action and processes of a computer system, orsimilar electronic computing device, that manipulates and transformsdata represented as physical (electronic) quantities within the computersystem memories or registers or other such information storage,transmission, or display devices.

Additional advantages will be readily apparent to those skilled in theart from the following detailed description. The examples anddescriptions herein are to be regarded as illustrative in nature and notrestrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments are described with reference to the accompanyingfigures, in which:

FIG. 1 illustrates an example of a simplified legal citation network.

FIG. 2 illustrates a heatmap of the U.S.C.

FIG. 3 illustrates a heatmap of the C.F.R.

FIG. 4 illustrates the amount of internal and external citations forvarious titles of the U.S.C.

FIG. 5 illustrates the amount of internal and external citations forvarious titles of the C.F.R.

FIG. 6 illustrates the amount of public law citations to U.S.C. titlesfor the various Congresses.

FIG. 7 illustrates the amount of U.S.C. citations from FederalRegulations.

FIG. 8 illustrates the amount of citations for various C.F.R. titles forvarious federal agencies.

FIGS. 9A-9B illustrate a heatmap for various federal agencies C.F.R.responsibilities.

FIG. 10 illustrates a user interface where a search was performed forlooking at parts of the IRS Code that deal with confidentiality ofinformation.

FIG. 11 illustrates a user interface where a local neighborhood around aparticular is displayed.

FIG. 12 illustrates the zoomed in interface of FIG. 11.

FIG. 13 illustrates a user interface that provides an example of theimpact a public law has on an agency.

FIG. 14 illustrates a user interface showing the results of a queryrelated to H.R. 1314.

FIG. 15 illustrates a user interface showing the results of a queryrelated to 26 U.S.C. 6103.

FIG. 16 illustrates a user interface showing the results of a queryrelated to the VA Choice Act.

FIG. 17 illustrates a user interface showing additional results of aquery related to H.R. 1314.

FIG. 18 illustrates an example user interface of the web-basedapplication disclosed herein.

FIG. 19 illustrates an example of a computer in accordance with oneembodiment.

DETAILED DESCRIPTION

Laws, regulations, and policies that govern federal agencies are sointertwined and interdependent that the operation impact of changes oradditions to them are often poorly understood or appreciated at both thelegislative and operational stage. Applicants discovered that networkmodels can provide agencies a more objective and transparent view oftheir LRPs and be used to study potential policy impacts on agencies.More specifically, Applicants have developed a legal path analysissystem that can leverage network models of legal text to efficientlyevaluate the impact of legislation on U.S. federal government agencies.More specifically, the system and methods disclosed herein can helpdetect impactful laws, regulations, and policies before they areimplemented, can automate traceability of legal requirements, and/or canhelp identify superseded policies for government agencies.

As stated above, searching the immense and ever expanding amounts ofLRPs for LRPs that directly impact a government agency iscomputationally inefficient. However, Applicants discovered that thelegal system can be modeled as a network with the legal text (e.g.,titles, chapters, sections, and clauses of the United States Code(U.S.C.)) and citations within corresponding to the entities (or nodes)and relationships (or edges), respectively. Using such an approach, theinterconnected set of bills, public laws, rules, statutes, U.S.C., Codeof Federal Regulations (C.F.R.), etc. can be treated as a network toexplore the chain of changes that result from new legislation. Thislegal network can be stored as a graphing database.

In network science, this can be referred to as path analysis. Such apath can be defined as a sequence of edges that connect a sequence ofnodes. This path analysis can assess, given the paths of nodes and edgeslinked from a legislative act, the agencies that are associated with thelegislative act to infer potential impact of the legislation on theagency. To perform such an analysis, Applicants developed a databasedriven web application to model the citation network. This webapplication can perform automated download, citation extraction, andingestion for each of the collective legal corpora. Furthermore, theweb-based application can explore the legal network based on topic orstructure of the legal text, as well as perform path analysis.

In the context of the present application, the nodes can be legal texts,sections of legal texts, government agencies, and/or legal texts ofgovernment agencies. Governmental agencies can be nodes connected toother legal text nodes because the agency may have created thecorresponding legal text or the legal text may govern the operation ofthe agency. Legal texts include, but are not limited to, public laws,Congressional legislation (e.g., federal bills), the United States Code(U.S.C.), the Code of Federal Regulations (C.F.R), Federal Rules, andExecutive Orders (including presidential directives). These legal textscan be obtained from the government publishing office website. A list ofgovernment agencies can be combined from USA.gov,FederalRegulations.gov, and C.F.R. Chapter Headings.

In the context of the present application, the edges can be citations.In addition, citations to agencies can be created when LRPs mentionedagencies or cited parts of the LRPs that an agency regulation dependson.

Creating the Legal Citation Network

The citation network of laws and regulations can be a representation ormodel of the legal system. Although the legal system is vast and denselyinterconnected, the citation network can represent the relationshipsbetween parts of the law, including the relationship that laws have toregulations. Further, by relating parts of the C.F.R. and U.S.C. toagencies, the relationships that laws have to the agencies thatimplement them can be determined. These relationships can be used tounderstand the impact that new laws have on agencies, and can help toidentify which regulations will need to be updated due to a new law. Forexample, the citation network can utilize citation-based relationshipsto associate parts of the C.F.R., the U.S.C., and public laws or federalbills to federal agencies.

An example of an oversimplified legal citation network is illustrated inFIG. 1. The various relationships between bills in Congress, publiclaws, the U.S.C., the C.F.R., and agency strategies, manuals, and formsare shown in FIG. 1. The circles represent various nodes for eachsection of the given legal texts on the right. The dotted linesrepresent a citation from one section of a legal text to another sectionof a different legal text and the solid lines represent a citation fromone section of a legal text to another section of the same legal text.Accordingly, the citation network can provide visualization for thevarious interactions between legal texts.

Creating Nodes

In some embodiments, nodes can be created in the citation network for atleast one of: (1) the federal agencies; (2) the Code of FederalRegulations; (3) the United States Code; (4) federal public laws; (5)federal bills; (6) Federal Rules; and (7) Executive Orders. In someembodiments, a node for at least one federal agency can be created inthe citation network.

In some embodiments, a node can be created for each federal agency ofthe U.S. federal government. A list of government agencies can becompiled from USA.gov, FederalRegulations.gov, and C.F.R. ChapterHeadings. In some embodiments, a node can be created for an agency'spolicies and regulations (e.g., agency strategies, manuals, and forms).In such a case, an edge can be created between an agency node and theagency's policy and regulation node.

In some embodiments, a node for at least one title of the United StatesCode can be created in the citation network. In some embodiments, a nodefor each title of the United States Code can be created in the citationnetwork. In some embodiments, a node can be created for a subsection ofthe U.S.C. other than title (e.g., subtitle, chapter, subchapter, part,subpart, section subsection, paragraph, subparagraph, clause, subclause,item, and/or subitem). In such a case that a node is created for asubsection of another section of the U.S.C., an edge can be createdbetween the section node and its subsection node. For example, if atitle node and a subtitle node of the U.S.C. is created, an edge betweenthe two can also be created. In addition, if a chapter node, subchapternode, and part node are created, an edge between the chapter node andthe subchapter node and an edge between the subchapter node and the partnode can also be created.

In some embodiments, a node for at least one title of the C.F.R. can becreated in the citation network. In some embodiments, a node for eachtitle of the C.F.R. can be created in the citation network. In someembodiments, a node can be created for a subsection of the C.F.R. otherthan title (e.g., subtitle, chapter, subchapter, part, subpart, sectionsubsection, paragraph, subparagraph, clause, subclause, item, and/orsubitem). In such a case that a node is created for a subsection ofanother section of the C.F.R., an edge can be created between thesection node and its subsection node.

In some embodiments, a node for at least one federal public law can becreated in the citation network. In some embodiments, a node for eachfederal public law can be created in the citation network. In someembodiments, a node can be created for a subsection of the federalpublic law. In such a case that a node is created for a subsection ofthe federal public law, an edge can be created between a section of thefederal public law node and its subsection node.

In some embodiments, a node for at least one federal bill can be createdin the citation network. In some embodiments, a node for each federalbill can be created in the citation network. In some embodiments, a nodecan be created for a subsection of the federal bill. In such a case thata node is created for a subsection of the federal bill, an edge can becreated between a section of the federal bill node and its subsectionnode.

Creating Edges

In order to create additional edges in the citation network, thecitations between the various legal texts needs to be determined. Forexample, a portion of Title 35 of the U.S.C. may cite to title 7 of theC.F.R. As such, an edge between the title 35 U.S.C. node and title 7C.F.R. node can be created.

In some embodiments, citations to the U.S.C. in the C.F.R., citations tothe public laws in the C.F.R., citations to Congressional legislation(e.g., federal bills) in the C.F.R., citations to Federal Rules in theC.F.R., and/or citations to Executive Orders in the C.F.R. can bedetermined. In some embodiments, citations to public laws in the U.S.C.,citations to Congressional legislation (e.g., federal bills) in theU.S.C., citations to the C.F.R. in the U.S.C., citations to FederalRules in the U.S.C., and/or citations to Executive Orders in the U.S.C.can be determined. In some embodiments, citations to Congressionallegislation in the public laws, citations to the U.S.C. in the publiclaws, citations to the C.F.R. in the public laws, citations to FederalRules in the public laws, and/or citations to Executive Orders in thepublic laws can be determined. In some embodiments, citations to publiclaws in Congressional legislation, citations to the U.S.C. inCongressional legislation, citations to the C.F.R. in Congressionallegislation, citations to Federal Rules in Congressional legislation,and/or citations to Executive Orders in Congressional legislation can bedetermined. In some embodiments, citations to public laws in the FederalRules, citations to Congressional legislation in the Federal Rules,citations to the U.S.C. in the Federal Rules, citations to the C.F.R. inthe Federal Rules, and/or citations to Executive Orders in the FederalRules can be determined. In some embodiments, citations to public lawsin Executive Orders, citations to Congressional legislation in ExecutiveOrders, citations to the U.S.C. in Executive Orders, citations to theC.F.R. in Executive Orders, and/or citations to the Federal Rules inExecutive Orders can be determined.

To determine the citations between the various legal texts, a citationparsing algorithm can be applied. The citation parsing algorithm can useregex patterns universally-applicable to all ingested documents andadded support to ingest corpora based on their independent structuresand file formats. Essentially, for every citation in a document, thecitation is recorded in the section that the citation was found as wellas the sections that the document is citing. These citations can formthe edges between the nodes (sections of the documents).

The process for parsing each legal document can rely upon two primaryfactors: (1) the file format of the document; and (2) the metadatastructure of the document. For example, U.S.C. documents have a definedset of levels at which freeform textual content resides, ranging fromthe Title (the entire document) to its Items (the lowest possible levelof the document, second only to Subitems residing in bulleted lists).All the constituent parts of a Title, including the Title itself, maycontain sub-component elements as well (e.g., Subtitle, Subchapter,Subitem, etc.). Knowing this set of possible components, Applicantsdeveloped an algorithm which extracted the citations from the legal textat each hierarchical level and encoded it into a list of documents. TheU.S.C. and C.F.R. corpora are available from the Government PublishingOffice in Extensible Markup Language (“XML”). The Applicants utilizedthe hierarchical encoding of the U.S.C. and C.F.R. in XML tagsassociated with each level, normalized the consistency of the set oftags across the U.S.C. corpora, and read the observed tags into a listof documents. Using recursion, Applicants programmatically identifiedwhether and in what sequential order those elements appears in eachingested document, tracing the parent-child relations of those elementsso that the structural hierarchy can be agnostic and automaticallydetermined per document rather than per corpus. As such, in cases wherecertain elements are interchangeable across a corpus, this can beuseful. For example, most U.S.C. documents have Parts which precedeChapters, but, in some cases such as Title 38, the Chapters may insteadprecede the Parts.

This process also allowed Applicants to accurately parse the C.F.R.,which has a different set of XML tags to correspond to its documentstructure levels and does not label any levels below the Section levelof the structure (although lower levels do formally exist in legislativeauthoring). Applicants have also determined the repeatability of thisprocess to Federal Congressional Bills, public laws, Executive Orders,Federal Rules, and internal policy documents for various federalagencies.

For documents where XML-labeled metadata is unavailable such as textfiles, PDFs, or XML documents without structured organization,Applicants were able to parse text at the highest level of the document,such as the Title, allowing Applicants to produce accurate, if sometimesimprecise, source-target reference data.

As the algorithm/program identifies a new level in a document, it canrecord its current position within the document for source-labelingpurposes (e.g., 8 U.S.C. 1, followed by 8 U.S.C. 2, etc.). This processcan parse each document ingested into the algorithm/program bypreserving and identifying its sequential ordering. It then can extractthe text relevant to that specific element without associating the textof any higher- or lower-level elements that have been tagged by XML.

With this approach, the text specific of the lowest-level elements ofany document can be recalled and associate that text with higher-levelparents as needed to reproduce as little or as much of the document asdesired. For citation extraction, the lowest-levels available can beused to maximize the precision of the policy reference system, and rollup to a higher-level in post-processing when consistency across corporaor comparison to other studies is the goal.

The text of each level can be scanned with an extensive set of regularexpressions tailored to identify the most common formatting patternsthat are used to cite legal documents. This can allow the program toidentify citations to various corpora, thereby maximizing the referencelist even before a citable corpus is prepared for ingestion. Inaddition, the use of a simple flagging system can also limit theextracted references to any specific subset of corpora deemed useful. Aspart of the regular expression parsing, references can be included thatuse more “natural language” formatting. Next, the data extracted canthen be reformatted into consistent labeling patterns. For example, “8U.S.C. 5” can also be referenced as “Section 5 of Title 8 of theU.S.C.”, but however the program extracts it from text, it can store itconsistently as “8 U.S.C. 5”. This can help prevent data duplication andcan further be enhanced by a very minor typographical-correction processincluded in the labeling stage.

The resulting data set can be a legal citation network inclusive of thesource corpora ingested and the cited corpora which has both writtenregular expression to identify and have chosen to store. The source of arelationship in the resulting network can be the lowest-level parsedwithin each document, the one for which textual content has beenextracted. The target (or recipient or tail-end) of the relationship canbe the actual reference made by the text, which can range from thehighest- to the lowest-levels of a legal document. Relationships can beweighted by the frequency with which a source makes reference to atarget, such that multiple references from one document to anothersuggest a strong dependency between them. This can be most notable whenthe labels are “rolled up” to higher levels and the relationshipsbetween documents at the Title or Section levels can be measured.

In response to determining a citation from one legal text to another, anedge can be created between at least two nodes of the legal texts. Forexample, if a node is created for a title of the U.S.C. and in thatsection of the U.S.C. that corresponds to the title there is a citationto a title of the C.F.R., an edge can be created between the title nodeof the U.S.C. and the title node of the cited C.F.R. In addition, if anode is created for a subtitle of the U.S.C. and in that section of theU.S.C. that corresponds to the subtitle there is a citation to asubsection of the C.F.R., an edge can be created between the subtitlenode of the U.S.C. and the subsection node of the C.F.R. As such,whenever a section of a first legal document cites to a section of asecond legal document, an edge can be created between the node thatcorresponds to the section of the first legal document and the node thatcorresponds to the section of the second legal document. This creationof edges between nodes can be applied to all node titles, subtitles,chapters, subchapter, part, subpart, section subsection, paragraph,subparagraph, clause, subclause, item, and/or subitem of the variouslegal documents. Accordingly, the citation network can map the variousinteractions between the various legal texts.

To construct a complete network of the legal system, the most up to daterelevant corpora of legal documents can be incorporated into thenetwork. Accordingly, the system disclosed herein can automaticallyingest the most updated revision of the U.S.C., C.F.R., public laws,Congressional bills, Executive Orders, Federal Rules, and other legaltexts. The majority of the federal legal corpora is available online inmachine-readable format, along with document metadata in various levelsof specificity. For example, current and some historic bills, publiclaws, status, the USC, Federal Rules, and many other official documentsare available in bulk from the Government publishing Office's FDSyssite.

As stated above, the legal system is vast and opaque. Specifically, thelaw is dynamic, nonlinear, interrelated, and constantly growing. Forexample, both the U.S.C. and C.F.R. contain thousands upon thousands ofwords. In addition, the individual sections of the U.S.C. and the C.F.R.are gigantic as well. FIGS. 2 and 3 provide a heatmap of various titlesof the U.S.C. and C.F.R., respectively, wherein the size of the box foreach title is consistent with the size of the corresponding section ofthe U.S.C. and C.F.R. for each title. Furthermore, there is an extremelylarge amount of both internal and external citations in the U.S.C. andthe C.F.R. FIGS. 4 and 5 illustrate the amount of internal and externalcitations for the U.S.C. and C.F.R., respectively, with respect tovarious titles of the U.S.C. and C.F.R. In addition, FIG. 6 provides anillustration on how the laws continuously adapt over time. Specifically,FIG. 6 illustrates the amount of public law citations to U.S.C. titlesfor the various Congresses. FIG. 7 illustrates the amount of U.S.C.citations from Federal Regulations.

As can be seen from these Figures, the amount of text and various crosscitations between the legal documents is enormous. Searching these vastand ever changing bodies of legal text is computationally inefficient.However, Applicants' citation network of nodes and edges for the variouslegal texts can be handled by a computer more efficiently.

Edges between nodes of federal agencies or federal agencies' policiesand regulations (e.g., operating manuals) and other nodes for legaltexts can also be created. In some embodiments, sections (titles,subtitles, etc.) of the U.S.C. and/or C.F.R. that are relevant to thefederal agencies can be determined. There are several ways to attempt toidentify which laws are relevant to an agency. One way can be to look atthe title and chapter headings of the C.F.R., which are named based onthe agency they pertain to. The Applicants developed a mapping betweenthe agencies named in the C.F.R. titles and the agency names that appearin the Federal Register. Another way to identify which agencies arerelevant to which parts of the U.S.C. and C.F.R. can be to look at theFederal Register. The Federal Register contains a collection of ruleswhich cite the parts of the C.F.R. that they are amending, as well asthe part of the U.S.C. that they are implementing. The Applicantscollected and extracted citations between the U.S.C. and the C.F.R.sections mentioned by each document in the Federal Register, andrecorded the network structure. Each rule in the Federal Register canalso be connected to the agency that issued the rule. This networkstructure could provide a representation of the interconnections betweenagencies, the U.S.C., and the C.F.R. In addition, the Public Laws andBills in Congress both cite parts of the U.S.C in their implementation,and can therefore be connected indirectly to the agencies that deal withthe same parts of the U.S.C. and C.F.R. that they do. Executive Orders,too, can cite parts of the C.F.R., and can therefore be connected torelevant agencies. Agencies can also be connected to all documents thatname them directly.

FIG. 8 illustrates the amount of citations for various C.F.R. titles forvarious federal agencies. In addition, FIGS. 9A-9B illustrate a heatmapfor various federal agencies' C.F.R. responsibilities, wherein thepattern of each box is for a single title of the C.F.R. and the size ofeach box is consistent with the size of the corresponding section of thetitle that the federal agency is responsible for.

Thus, the Applicants developed a system that can build such a networkwhich could be queried in such a way as to return all the connectionsbetween a document and an agency. This system can return the number ofconnections between a public law, the U.S.C., the C.F.R., and an agency,for instance. To connect a public law to an agency, for example, thereshould exist a “path”, or series of connections, between an agency, theC.F.R., the U.S.C., and the public law. The network can be queried insuch a way as to return all “paths” between any two nodes.

The intuition of this approach can be checked by examining the parts ofthe U.S.C. that are relevant to each agency. In Table 1 below, a set ofagencies, C.F.R. titles, and U.S.C. titles illustrate the topicalrelationship between the U.S.C. and C.F.R. In this fashion, agencies canbe associated with the C.F.R. and U.S.C. From there, any new public lawsor bills that cite a part of the U.S.C. can be associated with anagency.

TABLE 1 Agency CFR Titles USC Titles CENTERS FOR 42 26, 25, 32, 42, 5,31, 38, 10, MEDICARE AND 21, 20, 43, 41, 8, 18, 15, 29, MEDICAID 2, 45SERVICES ENVIRONMENTAL 40, 5, 2 42, 15, 21, 7, 5, 18, 16, 26, 20,PROTECTION 40, 43, 31, 6, 29, 28, 33, 50, 49, AGENCY 25, 48, 41, 23, 19,1, 30, 44, 46, 14 CENTRAL 32 50, 5, 42, 29, 18, 20, 21 INTELLIGENCEAGENCY INTERNAL 26 15, 42, 19, 5, 50, 22, 49, 6, 31, REVENUE 37, 2, 29,11, 43, 8, 38, 12, 30, SERVICE 46, 41, 45, 35, 28, 10, 7, 18, 26, 47,33, 25, 48, 13, 16, 21, 20 PATENT AND 37 35, 15, 28, 31, 18, 17, 5, 44,26, TRADEMARK 20, 42 OFFICE

An example of a citation network can be shown as follows: An edge can becreated between an agency node and the sections of the C.F.R. thatbelong to that agency. For the C.F.R. sections, various sections of theU.S.C. that it cites can then be identified and an edge can be createdbetween the U.S.C. sections and any agency connected to the C.F.R.sections. Next, for the various U.S.C. sections, public laws that itcites can be identified and an edge between the public law and anyagency connected to the U.S.C. sections can be created.

The impact to a given agency can be quantified using various metrics,such as the number of sections of the laws affecting the agency that areamended or modified as a result of the public law. These documents canbe organized into a hierarchical citation network and displayed in abrowser using a network visualization library. Laws and agencies can behighlighted, and colors can be used to differentiate the types of legalcorpora and the interaction between them. This network can provide anindication of the path of implementation of a given law by agencies.

Using the Legal Citation Network

The Applicants created a web-based application, referred to asPolicyNet, that can allow users to query the citation network in severalways. Most significantly, the citation network can query documents basedon their proximity to an agency. For example, a legal analyst can usePolicyNet to identify public laws, Executive Orders, and Bills inCongress that are likely to be relevant and impactful to an agency. Ananalyst can also use search tools in PolicyNet to search for documentsby topic, and identify the “local network” of any document in thenetwork. This can allow researchers to identify other agencies that agiven document may be connected to.

The citation network can also be used for exploring the network of laws,regulations, and policies, including a graph-based search and aneighborhood view of any node in the network. In addition, the systemand citation network can handle queries. For example, if a user asks thesystem to analyze the impact of a law on a specific agency, the systemwill query for that law's node. If that law is not already in thecitation network, then it will be added to the citation network. If thelaw is in the citation network, then the system can provide the parts ofthe U.S.C. that the law cites and the links to the various other legaltexts that are connected to that node via edges. Essentially, the systemcan provide all paths between that law's node and the agency's node. Inaddition, the system can provide all the parts of the laws andregulations that are going to be amended by this law or that are basedon this law.

Furthermore, in the systems disclosed herein, users can enter a PublicLaw and see all the laws, regulations, and policies that have cited thelaw. The network can also be organized hierarchically, such that theprovenance of changes is represented. As such, views of the data candemonstrate the magnitude of changes that a given law can create, andprovide an indication of the agencies and policies that are affected bythe law. The systems and methods disclosed herein, backed by a databaseof all public laws and regulations, can provide a generalized method toanswer empirical questions about regulatory impact. Furthermore, thesystem and methods disclosed herein can identify public laws or federalregulations that are relevant to federal agencies and createnotifications for the agencies and/or users. In addition, the system cananswer the following questions: (1) Which laws and regulations discuss agiven topic; (2) What is the regulatory implementation of a law; (3)What is the legal precedence for a regulation; and (4) Which bills,laws, orders, and regulations impact an agency.

The system disclosed herein can be in the form of a web-basedapplication. An example of the web-based application is shown in FIG.18. FIG. 18 displays a web page with a ‘toolbar’ at the top, a‘side-navigator’ on the left, and a ‘main view’ in the middle of thepage. The ‘toolbar’ has a search bar, which allows the user to specify atopic of interest, and an ‘edge slider’, which allows the user to selectthe number of network connections to return in the search results. The‘side navigator’ can provide links to other features of the web app,including the ‘local network search’ and the ‘Agency Early WarningSystem’. The ‘main view’ is displaying the search results, a set ofnetworks which correspond to different parts of the law dealing with thequery ‘brain injury’. The top pie charts show the types of documentsappearing in the network, including the C.F.R., U.S.C., and others. Thebottom pie chart shows the types of citations that appear in thenetwork, including ‘amended’, ‘defined’, ‘required’, and ‘authorized’.The user can also switch to a table view of this data, which lists thenames of each document displayed, as well as other characteristics aboutthe data.

The system can allow a user to search the legal citation network bycorpus (and section of corpus) and/or keyword and can identify whichlaws, regulations, and policies are relevant to the search. FIG. 10illustrates a user interface where a search was performed for looking atparts of the IRS Code that deal with confidentiality of information. Ascan be seen from the user interface, the system identified 26 U.S.C.6103 as a good candidate for investigation. In addition, the system canidentify which parts of the citation network deal with this topic, andwhat the types of relationships are between the various nodes in theportion of the citation network shown in FIG. 10 for example.

The system can also allow a user to search the local neighborhood arounda particular law, regulation, or policy to identify its legal basis andimplementation. FIG. 11 illustrates a user interface where a localneighborhood around a particular is displayed. The system can identifythe types of laws, regulations, and policies that cite or are cited bythe particular law, regulation, or policy. As shown in FIG. 11, sixpublic laws, 27 U.S.C. sections, and 28 C.F.R. sections were foundrelated to the given law. In addition, the user interface can allow auser to drill down into the neighborhood to identify which other laws,regulations, or policies are citing or are cited by the particular lawof interest. FIG. 12 illustrates such a drill down. Notice how theC.F.R. nodes in FIG. 12 cite the U.S.C. nodes.

The system can also perform an impact analysis of a new bill inCongress. When a bill is in Congress, it cites the existing law it willamend. Agencies often have to analyze the potential impact of a bill ornew law on their own regulations and policies. The system disclosedherein can allow a user to search a Bill in Congress and identify thechanges the bill will make to existing law. Such changes can bepresented in the form of a redlined version. This can be achieved byquerying the text of the bill, and extracting the citations to theU.S.C. From there, an algorithm is used to find, replace, and amend thecontents of the relevant U.S.C. sections with the new bill text.

The system can also identify relevant laws, regulations, and policiesfor a given agency or determine each federal agency associated with eachlaw, regulation, and/or policy. Given the thousands of new laws,regulations, and policies passed each year, it is difficult to identifywhich ones are relevant to a given federal agency. As such, the systemdisclosed herein can use the legal citation network to determine thevarious dependencies between agency rules and regulations and the lawsthat they are based on. As such, new bills, public laws, ExecutiveOrders, etc. that reference agency-relevant parts of the U.S.C. orC.F.R. can be flagged as being “relevant” to such agencies if they areclosely connected to them in the network. In addition, if a law,regulations, or policy mentions an agency by name, it can also bedetermined to be relevant to that agency. This information can bequeried to identify, for a given agency, the set of bills, public laws,etc. that are closely connected to the agency. Documents that areconnected in a number of different ways to an agency can be rankedhigher in the search results, and the type of connections can bedisplayed to the user. The user can then click on each of the documentsin the list, read their descriptions, and see their full networkconnections.

For example, FIG. 13 illustrates a user interface that provides theimpact a public law has on the Department of Veterans Affairs agency.Specifically, FIG. 13 illustrates the degree, U.S.C. impact, and C.F.R.impact of a public law on the Department of Veterans Affairs. The“degree” score indicates the number of distinct types of connections agiven law has to the agency. The U.S.C. Impact score can indicate thenumber of citations the public law makes to sections of the U.S.C. thatare connected to the agency. The C.F.R. impact score can indicate thenumber of C.F.R. sections that are connected to the agency and theU.S.C. sections cited by the public law

In addition, the systems and methods disclosed herein provide a novelway of evaluating the accuracy of agency impact predictions. In the U.S.regulatory system, agencies create regulations to update the C.F.R. inresponse to new laws. The final rules created by agencies representactual changes made to the C.F.R., and can therefore be compared topredictions to assess the actual impact of new laws. As such, using thesystem described herein, each public law can be assigned a set ofimpacted agencies, called set P. Then, a set of relevant final rules canbe found using the following criterion: (1) the final rule cites theparts of the USC that were cited by the public law; and (2) the finalrule was created within 2 years of the end of the Congress that createdthe law. Using the set of final rules that meet these requirements, theagencies that published the rules can become the set of agencies, A,that are actually impacted. By comparing the set of impacted agencies tothe set of predicted agencies, the precision and recall can be assessedfor each public law.

EXAMPLES

Applicants applied the disclosed system herein to several agenciesstrategic documents about the operational impact of new laws andregulations.

Example 1—IRS

The Bipartisan Budget Act of 2015 amends the U.S.C. Internal RevenueCode for audits of large-for-profit partnerships. Existing audit rulesare repealed and replaced with provisions for examinations to occur atthe partnership level, rather than at the partner level. Historically,changes in IRS audit rules have led to the emergence of new strategiesto circumvent the proposed regulations. Given the current estimated taxgap associated with flow through business entities such as partnershipsto be $90B, efforts to help anticipate areas for potentialnon-compliance are critical. Accordingly, Applicants sought out to seekanswers to the following questions utilizing their system: (1) Whatamendments/deletions/additions does H.R. 1314 make to existingpartnership audit sections detailed in the Internal Revenue Code?; and(2) What implications might these changes have to the Internal RevenueManual?

Accordingly, Applicants ingested the H.R. 1314 bill Title XI into theirsystem which parsed it and extracted references to U.S.C./C.F.R. and tosections of the Internal Revenue Manual. As shown in FIG. 14, Applicantsdiscovered that H.R. 1314 cites 13 sections of the Internal Revenue Code(26 U.S.C.), which form the legal basis for over 60 sections of theInternal Revenue Manual (IRM).

Example 2—IRS

26 U.S.C. 6103 establishes the rules that taxpayer data can only be usedfor tax administration purposes. Applicants sought to determine: (1)What provisions of 6103 exist to share tax payer data and under whatcircumstances?; and (2) How does specific sections of the 6103 apply inan operational context?

Applicants used the system to map the dependencies between the Section6103 rules and the IRS internal Revenue Manual. As shown in FIG. 15,Applicants discovered that several sections of the IRM deal withpartnerships, and point to U.S.C. sections on data sharing requirementsand restrictions. The system helped detect relevant IRS rules and theirlegal bases.

Example 3—Veterans Affairs

The Veterans Access, Choice, and Accountability Act of 2014 made majorchanges to how veterans' issues are managed by the Department ofVeterans Affairs, their sub-agencies, and healthcare partners.Applicants sought to determine how the VA Choice Act impacts existinghealthcare law.

Applicants used the system to ingest and parse through the VA Choice Actto extract references to the U.S.C./C.F.R. and create a view of the datathat enumerates dependencies arising fromamendments/deletions/additions. The system was able to provideApplicants with FIG. 16 which illustrates the impact of the VACAA in oneuseful visual interface.

Example 4—Veterans Affairs 2

The VA Web Automated Reference Materials System (WARMS) provides acollection of VA claim forms and policies for a variety of topics. Theseforms are based on VA Regulations (38 C.F.R.) which outline programs andtheir qualification requirements. With thousands of sections of hundredsof thousands of words in 38 C.F.R., the size prohibits manual searchtechniques. Applicants sought to determine: (1) Which sections are morerelevant to the VA Benefits forms?; and (2) Which parts of WARMS and theCFR deal with a given topic?

Applicants used the system to ingest and parse through H.R. 1314 billTitle XI to extract references to U.S.C./C.F.R. and to sections of theIRM. Applicants determined that 38 C.F.R. 3.400 and 3.500 are the mostcentral nodes in the 38 U.S.C. WARMS M21 sub-network as these deal withbenefits, apportionments, and discontinuances. Lastly, as shown in FIG.17, Applicants discovered that the VA Laws, Regulations, Policies, andForms dealing with claims relating to Agent Orange are spread across anumber of VA policies in WARMS, which have connections to the U.S.C.,C.F.R., public laws, and other VA forms.

Computer System

FIG. 19 illustrates an example of a computer in accordance with oneembodiment. Computer 1500 can be a component of a system forimplementing the web based application according to the algorithms,methods, and systems described above or can include the entire systemitself. In some embodiments, computer 1500 is configured to perform amethod for determining the impact of a federal public law or federalbill on a federal agency as described herein. Computer 1500 can be ahost computer connected to a network. Computer 1500 can be a clientcomputer or a server. As shown in FIG. 19, computer 1500 can be anysuitable type of microprocessor-based device, such as a personalcomputer, workstation, server, or handheld computing device, such as aphone or tablet. The computer can include, for example one or more ofprocessor 1510, input device 1520, output device 1530, storage 1540, andcommunication device 1560. Input device 1520 and output device 1530 cangenerally correspond to those described above and can either beconnectable or integrated with the computer.

Input device 1520 can be any suitable device that provides input, suchas touch screen or monitor, keyboard, mouse, or voice-recognitiondevice. Output device 1530 can be any suitable device that providesoutput, such as a touch screen, monitor, printer, disk drive, orspeaker.

Storage 1540 can be any suitable device that provides storage, such asan electrical, magnetic, or optical memory, including a RAM, cache, harddrive, CD-ROM drive, tape drive, or removable storage disk.Communication device 1560 can include any suitable device capable oftransmitting and receiving signals over a network, such as a networkinterface chip or card. The components of the computer can be connectedin any suitable manner, such as via a physical bus or wirelessly.Storage 1540 can be a non-transitory computer readable storage mediumcomprising one or more programs, which, when executed by one or moreprocessors, such as processor 1510, cause the one or more processors toperform methods described herein.

Software 1550, which can be stored in storage 1540 and executed byprocessor 1510, can include, for example, the programming that embodiesthe functionality of the present disclosure (e.g., as embodied in thesystems, computers, servers, and/or devices as described above). In someembodiments, software 1550 can include a combination of servers such asapplication servers and database servers.

Software 1550 can also be stored and/or transported within anycomputer-readable storage medium for use by or in connection with aninstruction execution system, apparatus, or device, such as thosedescribed above, that can fetch instructions associated with thesoftware from the instruction execution system, apparatus, or device andexecute the instructions. In the context of this disclosure, acomputer-readable storage medium can be any medium, such as storage1540, that can contain or store programming for use by or in connectionwith an instruction execution system, apparatus, or device.

Software 1550 can also be propagated within any transport medium for useby or in connection with an instruction execution system, apparatus, ordevice, such as those described above, that can fetch instructionsassociated with the software from the instruction execution system,apparatus, or device and execute the instructions. In the context ofthis disclosure, a transport medium can be any medium that cancommunicate, propagate, or transport programming for use by or inconnection with an instruction execution system, apparatus, or device.The transport readable medium can include, but is not limited to, anelectronic, magnetic, optical, electromagnetic, or infrared wired orwireless propagation medium.

Computer 1500 may be connected to a network, which can be any suitabletype of interconnected communication system. The network can implementany suitable communications protocol and can be secured by any suitablesecurity protocol. The network can comprise networks links of anysuitable arrangement that can implement the transmission and receptionof network signals, such as wireless network connections, T1 or T3lines, cable networks, DSL, or telephone lines.

Computer 1500 can implement any operating system suitable for operatingon the network. Software 1550 can be written in any suitable programminglanguage, such as C, C++, Java, or Python. In various embodiments,application software embodying the functionality of the presentdisclosure can be deployed in different configurations, such as in aclient/server arrangement or through a Web browser as a Web-basedapplication or Web service, for example.

This application discloses several numerical ranges in the text andfigures. The numerical ranges disclosed inherently support any range orvalue within the disclosed numerical ranges even though a precise rangelimitation is not stated verbatim in the specification because thisdisclosure can be practiced throughout the disclosed numerical ranges.

The above description is presented to enable a person skilled in the artto make and use the disclosure, and is provided in the context of aparticular application and its requirements. Various modifications tothe preferred embodiments will be readily apparent to those skilled inthe art, and the generic principles defined herein may be applied toother embodiments and applications without departing from the spirit andscope of the disclosure. Thus, this disclosure is not intended to belimited to the embodiments shown, but is to be accorded the widest scopeconsistent with the principles and features disclosed herein. Finally,the entire disclosure of the patents and publications referred in thisapplication are hereby incorporated herein by reference

1. A method for determining the impact of at least one federal publiclaw on a federal agency, the method comprising: creating a citationnetwork comprising: creating a node for at least one federal agency; anode for at least one title of the Code of Federal Regulations (CFR), anode for at least one title of the Code of Laws of the United States ofAmerica (U.S.C.), and a node for at least one federal public law;determining titles of the CFR that are relevant to the at least onefederal agency; in response to determining titles of the CFR that arerelevant to the at least one federal agency, creating an edge betweenthe corresponding determined CFR title node and the correspondingfederal agency node; determining citations to the U.S.C. in the CFR; inresponse to determining a citation to the U.S.C. in the CFR, creating anedge between the corresponding cited U.S.C. title node and thecorresponding CFR title node; determining citations to federal publiclaws in the U.S.C.; and in response to determining a citation to federalpublic laws, creating an edge between the corresponding cited federalpublic law node and the U.S.C. title node; and determining the federalagency associated with the at least one federal public law using thecitation network.
 2. The method of claim 1, wherein determining thefederal agency associated with the at least one federal public law usingthe citation network comprises determining if edges exist: between thenode of the at least one federal public law and a node of a U.S.C.title; between the node of the U.S.C. title and a node of a C.F.R.title; and between the node of the C.F.R. title and a node of thefederal agency.
 3. The method of claim 1, further comprising in responseto determining that the edges exist between the node of the at least onefederal public law and the node of the U.S.C. title, between the node ofthe U.S.C. title and the node of the C.F.R. title, and between the nodeof the C.F.R. title and the node of the federal agency, displaying theedges and nodes between the at least one federal public law, the U.S.C.title, the C.F.R. title, and the federal agency.
 4. The method of claim1, wherein determining titles of the CFR that are relevant to the atleast one federal agency comprises determining federal agencies that arenamed in C.F.R. titles.
 5. The method of claim 1, wherein determiningtitles of the CFR that are relevant to the at least one federal agencycomprises determining citations to C.F.R. titles in rules in the FederalRegister and connecting a federal agency to a specific C.F.R. titlecited in a rule in the Federal Register issued by the federal agency. 6.The method of claim 1, further comprising receiving a request todetermine the impact of a first federal public law on a first federalagency.
 7. The method of claim 6, in response to receiving a request todetermine the impact of the first federal public law on the firstfederal agency, displaying a legal citation network comprising: an edgebetween a node of a first U.S.C. title and a node of the first federalpublic law cited in a section of the U.S.C. under the first U.S.C.title; an edge between a node of a first C.F.R. title and the node ofthe first U.S.C. title cited in a section of the C.F.R. under the firstC.F.R. title; and an edge between a node of a first federal agency andthe node of the first C.F.R. title that is relevant to the first federalagency.
 8. The method of claim 1, wherein creating a citation networkfurther comprises: creating a node for a federal bill; determiningcitations to the U.S.C. in the federal bill; and in response todetermining a citation to the U.S.C. in the federal bill, creating anedge between the corresponding cited U.S.C. title node and the federalbill node.
 9. The method of claim 8, further comprising determining afederal agency associated with the federal bill using the citationnetwork.
 10. The method of claim 1, wherein creating a citation networkfurther comprises: creating a node for an Executive Order; determiningcitations to the C.F.R. in the Executive Order; and in response todetermining a citation to the C.F.R. in the Executive Order, creating anedge between the corresponding cited C.F.R. title node and the ExecutiveOrder node.
 11. The method of claim 10, further comprising determining afederal agency associated with the Executive Order using the citationnetwork.
 12. A nontransitory computer readable storage medium storingone or more programs, the one or more programs comprising instructions,which when executed by an electronic device, cause the device to:receive a request to determine a federal agency associated with at leastone federal public law; create a citation network comprising: create anode for at least one federal agency; a node for at least one title ofthe Code of Federal Regulations (CFR), a node for at least one title ofthe Code of Laws of the United States of America (U.S.C.), and a nodefor at least one federal public law; determine titles of the CFR thatare relevant to the at least one federal agency; in response todetermining titles of the CFR that are relevant to the at least onefederal agency, create an edge between the corresponding determined CFRtitle node and the corresponding federal agency node; determinecitations to the U.S.C. in the CFR; in response to determining acitation to the U.S.C. in the CFR, create an edge between thecorresponding cited U.S.C. title node and the corresponding CFR titlenode; determine citations to federal public laws in the U.S.C.; and inresponse to determining a citation to federal public laws, create anedge between the corresponding cited federal public law node and theU.S.C. title node; and determine the federal agency associated with theat least one federal public law using the citation network.
 13. Anelectronic device, comprising one or more processors; memory; and one ormore programs, wherein the one or more programs are stored in the memoryand configured to be executed by the one or more processors, the one ormore programs including instructions for: receiving a request todetermine a federal agency associated with at least one federal publiclaw; creating a citation network comprising: creating a node for atleast one federal agency; a node for at least one title of the Code ofFederal Regulations (CFR), a node for at least one title of the Code ofLaws of the United States of America (U.S.C.), and a node for at leastone federal public law; determining titles of the CFR that are relevantto the at least one federal agency; in response to determining titles ofthe CFR that are relevant to the at least one federal agency, creatingan edge between the corresponding determined CFR title node and thecorresponding federal agency node; determining citations to the U.S.C.in the CFR; in response to determining a citation to the U.S.C. in theCFR, creating an edge between the corresponding cited U.S.C. title nodeand the corresponding CFR title node; determining citations to federalpublic laws in the U.S.C.; and in response to determining a citation tofederal public laws, creating an edge between the corresponding citedfederal public law node and the U.S.C. title node; and determining thefederal agency associated with the at least one federal public law usingthe citation network.